The present disclosure is related to the field of communication analytics, more specifically, the present disclosure is related o the identification of no-compliant communication interactions.
Many customer service interactions are driven by predefined scenarios and static rules that are triggered by actions or events that take place during a customer service interaction. These predefined scenarios may be presented in the form of scripts that have been created to convey particular information to the customer participating in the interaction. These scripts may be delivered by the customer service agent participating in the interaction, or may be automatedly delivered to the customer by playing a recording. Scripts can be implemented for internal best practices and quality control of a larger number of customer service interactions across multiple customer service agents. Other scripts may be designed in order to comply with external regulatory, legal, or other such requirements.
While the creation and implementation of scripts used in customer service interactions facilitate the goals of consistently providing effective and/or necessary information to customers in a manner determined to be a best practice, such implementation is only effective if the customer service agents incorporate the proper scripts in the appropriate scenario or in response to the appropriate triggering of events. Furthermore, the customer service agent must follow the script closely enough such that the purpose of the script, whether informative or otherwise, is achieved.
Therefore, in embodiments as disclosed herein, speech analytics of a customer service interaction are analyzed to identify customer service interactions in which a script or other standard message vas either incorrectly delivered, inappropriately delivered, or absent from a customer service interaction.